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Description
Machine Learning For Email: Spam Filtering And Priority Inboxll Indian Reprints of O'Reilly are printed in Grayscale.' webkit tap highlight color: transparent; color: rgb(102, 102, 102); font family: "Open Sans"; font size: 13px; margin top: 0px; margin bottom: 0px; padding: 6px 0px; background color: rgb(255, 255, 255);'If youre an experienced programmer willing to crunch data, this concise guide will show you how to use machine learning to work with email. Youll learn how to write algorithms that
ll Indian Reprints of O'Reilly are printed in Grayscale.'-webkit-tap-highlight-color: transparent; color: rgb(102, 102, 102); font-family: "Open Sans"; font-size: 13px; margin-top: 0px; margin-bottom: 0px; padding: 6px 0px; background-color: rgb(255, 255, 255);'If youre an experienced programmer willing to crunch data, this concise guide will show you how to use machine learning to work with email. Youll learn how to write algorithms that automatically sort and redirect email based on statistical patterns. Authors Drew Conway and John Myles White approach the process in a practical fashion, using a case-study driven approach rather than a traditional math-heavy presentation.'-webkit-tap-highlight-color: transparent; color: rgb(102, 102, 102); font-family: "Open Sans"; font-size: 13px; margin-top: 0px; margin-bottom: 0px; padding: 6px 0px; background-color: rgb(255, 255, 255);'This book also includes a short tutorial on using the popular R language to manipulate and analyze data. Youll get clear examples for analyzing sample data and writing machine learning programs with R.
Mine email content with R functions, using a collection of sample files
Analyze the data and use the results to write a Bayesian spam classifier
Rank email importance, using factors such as thread activity
Use your email ranking analysis to write a priority inbox program
Test your classifier and priority inbox with a separate email sample set
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